Profile
Who am I?
Greetings! My name is Steve Chan, and I am an Artificial Intelligence (AI)/Machine Learning (ML) Solution Architect and Numerical Algorithms Software Engineer. My research and engineering interests are primarily in the areas of AI, ML, numerical algorithms, data analytics, and decision science.
For the past several years (2016-2020), my engineering work has principally occurred "in the field;" the work has ranged from practical engineering to advanced AI/ML experimentation. Suffice it to say, although extremely challenging, the learning opportunities were invaluable, and the practical research and operationalization pathways nicely progressed through various Technology Readiness Level (TRL) stages. During this fieldwork period of time, 16 of my papers were accepted/published by refereed IEEE venues and 2 of my papers were published as Springer book chapters.
Prior to this fieldwork (2007-2016), I mostly worked in labs or basement-level datacenters, and coding seems to be at the heart of everything I did. I have had numerous functional roles ranging from that of a Lab Technician coding in Hardware Description Languages (HDLs) to a Unix/Linux administrator coding in Mathematical Programming Languages (MPLs). During the course of constructing various technology stacks, the programming languages utilized have been numerous and varied, and I have had extensive experience with handling deprecations (accompanied by numerous all-nighters).
Pathway to becoming an AI/ML Solution Architect
Since 2005, my core research has principally centered around translational biomimetics (a.k.a., nature-inspired engineering). This provided a robust foundation for my AI adventures, and looking back, the pathway was fortuitous, particularly given the fact that my research into neural network pathways (in nature) nicely dovetailed with, and allowed me to innovate with regards to, various deployments of artificial neural networks over the years; these include Convolutional Neural Networks (CNNs), Deep Convolutional Generative Adversarial [Neural] Networks (DCGANs), and the like.
I am grateful for the opportunities, which I have had. They have prepared and nurtured the versatility that I now have in tackling ML and DL challenges as well as the associated research and engineering complexities.
I remain a dedicated researcher, and I am always striving to learn and contribute to society-at-large.
About This Site
This site was initially constructed in August 2015 when GitHub Desktop was first made available. The content, at that time, was intended more as notations to self, and the formatting left something to be desired. Since that time, the style of the site has gone through several iterations and has now been migrated to that of an online GitHub site.
The main purposes of this site are to:
- Present some of the mathematics and the numerical algorithmic implementation intricacies of Machine Learning (ML) and Deep Learning (DL), which I have encountered.
- Delineate some of the implementation challenges for the ML/DL projects, which I have been engaged in.
- Illuminate some of the interim findings from my ML and DL journey.
Citations
If you would like to cite the blog posts and/or publications presented, via this site or repositories on my GitHub, please use the relevant Uniform Resource Locator (URLs) or Digital Object Identifiers (DOIs), which are provided for your convenience.
Contact Me
If you are interested in my advising or collaborating, please contact me via email.
If you have any questions or have encountered a technical issue, please open a ticket here, as it is difficult to track individual issue tickets related to my various repositories across GitHub, GitLab, GitKraken, etc., which I have utilized during the course of my journey. This will also be beneficial for all the followers/readers of this site and optimize my response time. Thank you in advance. If the ticket system is down, it likely means that I have become overwhelmed (as this site is a personal side endeavour), so apologies in advance.